Participatory design of mhealth strategies to support perinatal depression care for vulnerable populations

There is a pressing need to extend the reach of services for perinatal depression to low income women by addressing patients' economic, social, and cultural barriers as well as limited resources in the system of care serving them. mHealth interventions capitalize on the prevalent patient use of mobile phones and hold promise as effective strategies to assist and enhance the delivery of depression care to low income women. Patient centered care including eliciting patient preferences and reviewing treatment options could be delivered through HIIT platforms which are both less resource intensive for the health care delivery site and more guideline consistent than human providers alone. Despite promise, these approaches can only be successful if they are accepted by key patient and clinician stakeholders. We employed a participatory design and rapid prototyping approach to the development of clinical decision support and mHealth intervention prototypes to support the monitoring, adherence assessment/support, and clinical feedback functions of care managers working with low-income women with perinatal depression. Three participatory design groups comprised of patients with history of depression in pregnancy and prenatal providers including midwives, physicians, care managers, and mental health specialists were developed to identify specific targets and to work with programmers and researchers to design an HIIT system. These design groups reviewed potential targets and chose a hybrid treatment selection support and mHealth system to reinforce selected treatments. Review of available treatments for perinatal depression identified three primary axes of selection criteria; 1) efficacy, 2) risk, and 3) convenience. Evidence for each of these dimensions will be used to define the interactive algorithms for the planned system. SMS text and interactive voice response (IVR) messages will be designed by these participatory design teams to support treatment choices that will be enacted by the clinical team with patients.